In general, comparing two continuous densities is difficult because they
can differ on a set of measure 0 (i.e., at a single point) and yet have
the same distribution function.
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
On Behalf Of Chang Jia-Ming
Sent: Friday, D
The TRUE/FALSE vs. T/F issue brings up a related one. Can one assign a
variable a value during an R session that cannot be re-assigned any new
value during the session? That is, the variable is `protected' from
change during the session. `Session' here is not precisely defined, so
that will i
Neola
I'm a bit rusty on this, but I believe you can conduct on singular-value
decomposition on the 436 by 518 matrix. The squares of your singular values
(max of 436, 518-436 will be zero) will be your eigenvalues, the same as in the
PC analysis. The post-eigenvectors will be your components.
Stefan
You are right. Briefly put, the existence of 7 requires only Peano's
axiom for successive integers. Strictly speaking, 7 is not an integer
but a natural number. But natural numbers can be embedded in the
integers which can be embedded in the rationals which can be embedded
the reals which
Isn't the binomial-log used to obtain risk ratios from the coefficients
rather than odds-ratios?
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
On Behalf Of Thomas Lumley
Sent: Wednesday, September 10, 2008 4:36 PM
To: Prof Brian Ripley
Cc: r-help@r-project.org; Ben
Although I along with the other believe there probably is an efficient R
solution, the answer to your direct question can perhaps be found at
http://www.fortran.com/. The free GNU G95 fortran compiler is at
http://www.g95.org/
Joe
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL
And to follow FH and HW
What level of significance are you using? .05 is excessively liberal.
Are you adjusting your p-values for the number of possible models? Do
you realize the p-values for dropping a term, being selected as the
maximum of a set of p-values, do not follow their usual distributi
Frank, I believe, is correct. Using the AIC/BIC for data-driven model
selection does NOT solve the "stepwise problem". This is because the
distribution of the sample AIC is changed from its original distribution to an
extreme-value distribution, e.g.., min (AIC1, AIC2, ..., AICn). Thus, whatev
fp0 = "C:\\Documents and Settings\\myname\\My Documents\\Research\\" #upper
file path
fp1 = "PIname\\PIproject\\Working00\\"
#middle file path
fp2 = "DateData\\Dates.xls"
#lower file path
dbase = f
First compute side-by-side boxplots for the two data sets. You will see
that the PG group has one (189), maybe 2 (also, 52) extreme values
whereas the PG group has none. The PG group will have a smaller median
than the PB group. Means, st devs, and se's are legitimate statistics
but do not have
Use lchoose and use logarithms throughout.
> x=666
> y=1287
> lchoose(x+y,x)-(x+y)*log(2)
[1] -104.4265
> Pxy = exp(lchoose(x+y,x)-(x+y)*log(2))
[1] 4.447787e-46
Joe
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
On Behalf Of Hyojin Lee
Sent: Monday, February 18,
round(12.01,1) will give the answer 12, not 12.0 or even 12. To make a
table look nice, I need to display the trailing zero so that just as
round(12.05,1) yields 12.1, round(12.01) yields 12.0. I cannot find an
answer in print() or format() or options(). Any suggestions would be
appreciated.
Jose
A good summary of the differences between S-PLUS and SAS, along with
their respective advantages and disadvantages, is given in Section 1.6
of http://lib.stat.cmu.edu/S/Harrell/doc/splusp.pdf.
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
On Behalf Of bogdan romoce
chol(B) doesn't give the original A, which I believe is what Mike wants.
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
On Behalf Of Katharine Mullen
Sent: Wednesday, October 31, 2007 4:08 PM
To: Michael Gormley
Cc: [EMAIL PROTECTED]
Subject: Re: [R] Find A, given B
The classic way to test for better fit with an additional variable is to use
the anova() function. The model must have the suspect variable listed last
into your model. The anova() function will give you the correct sequential
decomposition of your model effects and their conditional (F or t)
15 matches
Mail list logo